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Miyu Oba

Miyu Oba has 2 papers in our library, in 2023–2026, most of them on Language models & pretraining, Evaluation & benchmarks, Psycholinguistics & language acquisition; often with Saku Sugawara, Yohei Oseki.

2 papers in our library · 2023–2026

OpenAlex · h-index 3 · 22 works · 16 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 9 times in our library · ⭐ Paper Stars ranking: #10056

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Nara Institute of Science and TechnologyIkoma · Japan2022–2026 · 27 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksDevelopmental and Educational Psychology · 2 worksLanguage and Linguistics · 2 worksPsychology · 2 works

🧭 Topics 3Research subjects and languages the work is about.Psycholinguistics & language acquisition · 1 workEvaluation & benchmarks · 1 workLanguage models & pretraining · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Child-directed speech · 1 work

 Works by year

2020s

20261 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. BabyLM Challenge: Curriculum learning based on sentence complexity approximating language acquisition (2023 · 9 citations)
    The BabyLM Challenge is a shared task in which language models are trained on a small corpus. Its size approximates the amount of language a child hears at an early age. The authors built on the fact that adults first speak to young children in simple, short phrases, and the complexity of speech increases as the…
  2. CxMP: A Linguistic Minimal-Pair Benchmark for Evaluating Constructional Understanding in Language Models (2026)
    Most linguistic evaluations of language models check whether a model can tell grammatical sentences from ungrammatical ones. They rarely test whether it grasps the meaning that a grammatical form carries. CxMP addresses this gap using Construction Grammar, which views constructions as pairings of form and meaning.

 Co-authors here

2 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 9 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated

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